A hierarchical recurrent Siamese network with a two-threshold contrastive loss raises authorship verification accuracy on a social-media benchmark from about 71% to 85.3%.
A hallmark of such systems is that the true identity of anyone accessing the sys tems is typically not verified
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Similarity Learning for Authorship Verification in Social Media
A hierarchical recurrent Siamese network with a two-threshold contrastive loss raises authorship verification accuracy on a social-media benchmark from about 71% to 85.3%.